个人简述:

代琦 博士、副教授、硕士生导师、科研实验中心主任、生物信息学学科组主任。2009年5月受聘于杭州电子科技大学生物医学工程与仪器研究所，2010年破格晋升副研究员，2011年调职到浙江理工大学生命科学学院。2008年荣获2006届博士生专项奖学金---“纪念向坊隆”村井隆奖学金，2011年入选浙江省“151”人才第三层次，2012年入选浙江省高校中青年学科带头人；2013年入选浙江理工大学“521”拔尖人才。主持国家自然科学基金项目3项、浙江省自然科学基金1项，其中包括国家自然科学基金青年-面上连续项目1项。发表各类科研论文35篇，其中SCI期刊收录35篇（第一作者SCI论文18篇，其中2区7篇）。开发生物学软件4个，共下载次数2000余次。2010年至今，担任国际期刊《Computational and Mathematical Methods in Medicine》（SCI期刊），《JournalofComputationalBiologyandBioinformaticsResearch》,《AmericanJournalofBioinformaticsandComputationalBiology》编委，浙江省生物信息学学会理事，浙江省信号处理学会会员。

科研工作:

一、科研项目

1.“联合序列结构特征和临床信息的多步修正宫颈癌HPV分型模型研究”国家自然科学基金，2014.1- 2017.12, 78万（负责人）

2.“与肿瘤蛋白质结构、功能有关的信息处理问题研究” 国家自然科学基金，基金号：61170316，2012.1- 2015.12, 52万（负责人）

3.“面向宫颈癌HPV分型模型的生物序列比较及分类方法研究”国家自然科学基金，基金号：61001214，2011.1- 2013.12, 24万（负责人）

4.“融合临床突变与序列的多重信息研究乳腺癌BRCA1/2基因突变区域”浙江省自然科学基金，基金号：Y2100930，2011.1- 2013.12, 10万（负责人）

5.“卵巢癌化疗反应基因标志物辨识研究”浙江省自然科学基金，基金号：Z2090299，2010.1- 2012.12, 35万（主要成员，3/7）

6.“与生物序列结构、功能有关的数学方法研究”，国家自然科学基金，基金号：10871219，2009.1- 2011.12, 23万（参与成员，6/9）

7.“数学方法在计算分子生物学中的应用”，国家自然科学基金，基金号：10571019，2006.1- 2008.12, 24万（参与成员，8/9）

二、发表论文

1.Qi Dai*, Yan Li, Xiaoqing Liu, Yuhua Yao, Yunjie Cao, Pingan He. Comparison study on statistical features of predicted secondary structures for protein structural class prediction: From content to position.BMC Bioinformatics, 2013, 14: 152.

2.Qi Dai*,Xiaoqing Liu, Yuhua Yao, Fukun Zhao. Using Markov model to improve word normalization algorithm for biological sequence comparison.Amino Acids, 2012, DOI 10.1007/s00726-011-0906-2.

3. Qi Dai*, Xiaodong Guo, Lihua Li.Sequence comparison via polar coordinates representation and curve tree.Journal of Theoretical Biology, 2012, 292: 78-85.

4.Qi Dai*, Lihua Li, Xiaoqing Liu, Yuhua Yao, Fukun Zhao, Michael Zhang. Integrating Overlapping Structures and Background Information of Words Significantly Improves Biological Sequence Comparison.PLOS one, 2011. 6(11): e26779.

5.Qi Dai*, Wu Li, Lihua Li.Improving protein structural class prediction using novel combined sequence information and predicted secondary structural features.Journal of Computational Chemistry, 2011, 32: 3393-3398.

6.Qi Dai*, Xiaoqing Liu, Yuhua Yao, Fukun Zhao. Numerical characteristics of word frequencies and their application to dissimilarity measure for sequence comparison.Journal of Theoretical Biology, 2011, 276(1): 174-180.

7.Xiaoqing Liu,Qi Dai*, Lihua Li, Zerong He.An efficient binomial model-based measure for sequence comparison and its application.J Biomol Struct Dyn,2011, 28(5):833-843.

8.Xiaoqing Liu,Qi Dai*, Lihua Li, Zhilong Xiu.Resistant mechanism against nelfinavir of subtype C human immunodeficiency virus type 1 proteases.Journal of Molecular Structure, 2011, 986: 30-38.

9.Qi Dai*, Xiaoqing Liu, Lihua Li, Yuhua Yao, Bin Han, Lei Zhu. Using Gaussian Model to Improve Biological Sequence Comparison.Journal of Computational Chemistry, 2010, 31: 351-361.

10.Shuyan Ding,Qi Dai, Hongmei Liu, Tianming Wang. A simple feature representation vector for phylogenetic analysis of DNA sequences,Journal of Theoretical Biology,2010, 265(4):618-623.

11.Yuhua Yao*,Qi Dai, Ling Li, Xu-Ying Nan, Ping-An He, Yao-Zhou Zhang. Similarity/dissimilarity studies of protein sequences based on a new 2D graphical representation.Journal of Computational Chemistry, 2010, 31(5): 1045-1052.

12.Qi Dai*, Yanchun Yang, Tianming Wang. Markov model plus k-word distributions: A synergy that produces novel statistical measures for sequence comparison,Bioinformatics, 2008, doi: 10.1093/bioinformatics/btn436.

13.Qi Dai*, Tianming Wang. Comparison study on k-word statistical measures for protein: from sequence to 'sequence space'.BMC Bioinformatics, 2008, revised.

14.Qi Dai*, Tianming Wang. Use of linear regression model to compare RNA secondary structures, Journal of Theoretical Biology, 2008, 253(4):854-60

15.Qi Dai*, Tianming Wang. Use of statistical measures for analyzing RNA secondary structures,Journal of Computational Chemistry, 2008, 29: 1292-1305.

16.Yuhua Yao,Qi Dai, Xu-Ying Nan, Ping-An He, Zuo-Ming Nie, Song-Ping Zhou, Yao-Zhou Zhang. Analysis of similarity/dissimilarity of DNA sequences based on a class of 2D graphical representation ,Journal of Computational Chemistry, 2008, 29: 1632-1639.

17.Yuhua Yao,Qi Dai, Chun Li, Ping-An He, Xu-Ying Nan, Yao-Zhou Zhang. Analysis of similarity/dissimilarity of DNA sequences based on a class of 2D graphical representation ,Proteins: Structure, Function, and Bioinformatics, 2008, 10.1002/prot.22110.

18.Qi Dai*, Xiaoqing Liu, Tianming Wang. C(i,j) matrix: A better numerical characterization for graphical representations of biological sequences,Journal of Theoretical Biology, 2007, 247: 103-109.

19.Qi Dai*, Xiaoqing Liu, Tianming Wang, Vukicevic, Damir. Linear regression model of DNA sequences and its application,Journal of Computational Chemistry, 2007, 28: 1434-1445.

20.Qi Dai*, Xiaoqing Liu, Tianming Wang. Analysis of protein sequences and their secondary structures based on transition matrices.Journal of Molecular Structure-THEOCHEM, 2007, 803: 115-122.

21.Qi Dai*, Xiaoqing Liu, Tianming Wang. Numerical characterization of DNA sequences based on the k-step Markov chain transition probability .Journal of Computational Chemistry, 2006, 27: 1830-1842.

22.Qi Dai*, Xiaoqing Liu, Tianming Wang. A novel 2D graphical representation of DNA sequences and its application.Journal of Molecular Graphics & Modelling, 2006, 25: 340-344.

23.Xiaoqing Liu,Qi Dai, Zhilong Xiu, Tianming Wang, PNN-curve: A new 2D graphical representation of DNA sequences and its application.Journal of Theoretical Biology, 2006, 243: 555-561.

三、软件情况

1.PSCP-PSSE. An integrated computational software which implements sixteen statistical features of predicted secondary structures from content to position for protein structural class prediction ( http://bioinfo.zstu.edu.cn/PSCP-PSSE).

2.Mplusd. An integrated computational software which implements four statistical similarity measures proposed by us to measure the (dis)similarity of biological sequences.

3.SMPS-SS. An integrated computational software which implements six statistical measures for protein comparison, where the statistical measures are based on protein sequence or protein 'sequence space'.